Real Time Eye Gaze Tracking for Human Machine Interaction in the Cockpit
The Aeronautics industry has pioneered safety from digital checklists to moving maps that improve pilot situational awareness. Today, pilots deal with increasingly complex cockpit environments and air traffic densification. Here we present an intelligent vision system, which allows real-time human-machine interaction in the cockpits to reduce pilot’s workload.
The challenges for such a vision system include extreme change in background light intensity, large field-of-view and variable working distances. Adapted hardware, use of state-of-the-art computer vision techniques and machine learning algorithms in eye gaze detection allow a smooth, and accurate real-time feedback system.
The algorithmic pipeline for eye gaze tracking was developed and iteratively optimized to obtain the speed and accuracy required for the aviation use cases. The pipeline, which is a combination of data-driven and analytics approaches, runs in real time at 60 fps. The eye gaze tracking accuracy goes down to less than 1° for the cockpit instruments towards which an accurate eye gaze was required according to the use cases